In handwriting recognition systems, writing areas are usually marked with lines to guide the user in the placement of the writing. Writing entered by a user is captured by a digitizer and sent to a pattern matcher where the writing is then matched against prototype patterns which represent handwriting units (characters) which can be recognized by the system. As part of the matching process, the Cartesian coordinates of the writing as captured by the digitizer must be normalized to coincide with the prototype coordinate space.
Normalization of coordinates is an important factor in obtaining high recognition accuracy. Information used in the process of obtaining a correct normalization include measurements such as line spacing, and the location of the baseline. Due to the natural variations in writing style between users and within the writing of a single user, these values can vary significantly from those suggested by the lines provided by the system in the writing areas. Since the normalization is critical to the success of the pattern matching algorithm, it is required that handwriting recognition systems provide an accurate on-going estimation of line spacing, and baseline placement values to achieve high rates of recognition accuracy.
There are a number of patents and articles directed to handwriting recognition, each having certain advantages and disadvantages.
U.S. Pat. No. 4,024,500 to Herbst et al discloses a method and apparatus for effecting character segmentation in a cursive script handwriting analysis system which comprises obtaining the continuous x and y coordinates and the x and y velocities of a writing instrument forming said cursive character. Continuously averaging the x displacement associated with all the x and y extremal points of a handwritten character where the x or the y velocity equals zero. Successively examining the x displacement for each x-extremal and determining if the x displacement of said extremal exceeds a predetermined threshold value relative to the average x displacement of the current character and if so, indicating that said new extremal is located in the next character and that a segmentation mark should be placed at a predetermined distance along the ligature between the just analyzed extremal and the previously analyzed extremal. The results of this segmentation are then communicated to a character recognition mechanism whose efficiency and accuracy is greatly enhanced by said segmentation indication. The system, as designed, is also able to follow deviations from the baseline and mid-zone line as the writing progresses.
U.S. Pat. No. 4,845,768 to Kochert et al discloses an editing arrangement for character recognition which has a binary coded character stored in a X/Y-addressable image signal memory from which signals are first read out column-by-column, whereby a first character shadow is formed from the result by projection of successive columns respectively comprising black points onto the character baseline. The stored character pattern is then repeatedly read out in accord with a scanning at positive and/or negative oblique angles relative to the Y-axis until a minimum character shadow is produced. The scanned pattern yielding this minimum character shadow is then selected for further evaluation of the character.
U.S. Pat. No. 4,972,496 to Sklarew discloses a keyboardless entry computer system which includes a transparent input screen that generates positional information when contacted by a stylus, and a display screen mounted physically below the input screen such that a character that is displayed can be seen below the input screen. The system includes a computer that has been programmed to compile the positional information into Strokes, to calculate Stroke characteristics, and then compare the Stroke characteristics with those stored in a database in order to recognize the symbol drawn by the stylus. Key features of the system are: 1) transparent position sensing subsystem; 2) underlying display on which to mimic drawing of sensed positions and to show characters or symbols; 3) means to convert sensed positions first into plotted Points and then into recognized characters or symbols; and 4) means to "learn" to associate sensed input positions with a character or symbol.
IBM Technical Disclosure Bulletin, Vol. 25, No. 10, March 1983, pages 5111-5114, in an article entitled "Baseline Drift Correction of Handwritten Test" by J. Kim divides a given word into smaller units. Each unit is a box of equal width and high enough to enclose all the points that lie within its width. Such boxes are uniformly spaced over the word. Then it is possible to analyze the relative position of the boxes and detect how they go up or down. The average dy/dx of the boxes is the amount of drift, which will be used for correction.
According to the present invention, baseline, line spacing and character height information used in recognizing handwriting is estimated through extraction from previously recognized words and through heuristic application of clustering of stroke y-coordinate extreme points to improve handwriting recognition accuracy.